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Related Questions
- How do text generation models handle polysemous words?
- Can you explain the techniques used to disambiguate words with multiple senses in large language models?
- What strategies do text generation models use to handle out-of-vocabulary (OOV) words with multiple possible meanings?
- How do models like word2vec and BERT handle polysemous words in their embeddings?
- Can you discuss the role of context in disambiguating words with multiple senses in text generation models?
- What are the challenges and limitations of using word embeddings to represent polysemous words?
- How do text generation models handle homograph words, and what techniques are used to disambiguate them?
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